Christopher Plaisier, Assistant Professor of Biomedical Engineering at the Ira A. Fulton Schools of Engineering at Arizona State University, and Samantha O’Connor, PhD student in Biomedical Engineering at Plaisier Lab, are leading research on a new stage in the stem cell life cycle that is key to unlocking new ones Methods to treat brain tumors could be. Her work was recently published in the research journal Molecular Systems Biology.
“The cell cycle has been studied so well and yet we are looking at it for the umpteenth time and a new phase appears,” says Plaisier. “Biology always has new insights to offer, you just have to look.”
The spark for this discovery came through a collaboration with Patrick Paddison, an associate professor at the Fred Hutchinson Cancer Research Center in Seattle, and Dr. Anoop Patel, an assistant professor of neurological surgery at the University of Washington, who is also at the Fred Hutchinson Cancer Research Center.
Paddison’s team asked Plaisier to help them analyze their brain stem cell data, which was characterized through a process called single cell RNA sequencing.
“These data turned out to be pretty amazing,” says Plaisier. “It’s mapped into this beautiful circular pattern that we’ve identified as all of the different stages of the cell cycle.” O’Connor has developed a new tool for classifying the cell cycle – called ccAF or ASU / Fred Hutchinson Cell Cycle – to illustrate the collaboration between the two institutions – that takes a more detailed, “high-resolution” look at what is happening within the growth cycles of stem cells and identifies them Genes that can be used to track progress through the cell cycle.
“Our classifier goes deeper into the cell cycle because we could capture parts that have important effects on disease,” says O’Connor.
When Plaisier and O’Connor used the ccAF tool to analyze cell data for glioma tumors, they found that the tumor cells were often in either G0 or G1 neural growth states. And as tumors become more aggressive, fewer and fewer cells remain in the resting neural G0 state. This means that more and more cells proliferate and allow the tumor to grow.
They correlated these data with the prognosis for patients with glioblastoma, a particularly aggressive brain tumor. Those with higher neural G0 levels in tumor cells had less aggressive tumors.
They also found that the resting neural G0 state is independent of a tumor’s rate of proliferation or how quickly its cells divide and form new cells.
“That was an interesting finding from our results, that rest itself could be a different biological process,” says Plaisier. “It’s also a potential point where we could look for new drug treatments. If we could put more cells into this dormant state, the tumors would be less aggressive.”
Current cancer drugs focus on killing cancer cells. However, when the cancer cells are killed, they release debris into the area around the tumor, which can make the remaining cells more resistant to the drugs.
“Instead of killing the cells, it could potentially be a much better situation if we put them to sleep,” says Plaisier.
With their ccAF tool, they were also able to find new states at the beginning and at the end of the cell cycle that exist between the well-known states. These are, among other things, the topics for their next research phase.
“We’re starting to think about how we can study these and learn more about the biology of entry and exit from the cell cycle, as these are potentially really important points where cells either go into the G1 or G0 states will be passed over, ”says Plaisier.
Finding out what causes a cell to enter the cycle of division or remain in a G0 dormant state could help understand the processes behind tumor growth.
“The main characteristic of any cancer is that the cells multiply,” says Plaisier. “If we could get in there and find out what the mechanisms are, this could be a place to slow them down.”
Plaisier and O’Connor are making the ccAF classifier tool open source and available in a variety of formats to anyone studying single cell RNA sequencing data to facilitate the process of studying cell cycles.
Reference: O’Connor SA, Feldman HM, Arora S, et al. Neural G0: a rest-like state found in neuroepithelial cells and gliomas. Mol. No. Syst. Biol 2021; 17 (6): e9522. doi: 10.15252 / msb.20209522
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